This paper describes the system that LCC has devised to perform textual entailment recognition for the PASCAL RTE Challenge. Our system transforms each text-hypothesis pair into a two-layered logic form representation that expresses the lexical, syntactic, and semantic attributes of the text and hypothesis. A large set of natural language axioms are constructed for each text-hypothesis pair that help connect concepts in the hypothesis with concepts in the text. Our natural language logic prover is then used to prove entailment through abductive reasoning. The system's performance in the challenge resulted in an accuracy of 55%. © Springer-Verlag Berlin Heidelberg 2006.
CITATION STYLE
Hodges, D., Clark, C., Fowler, A., & Moldovan, D. (2006). Applying COGEX to recognize textual entailment. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3944 LNAI, pp. 427–448). https://doi.org/10.1007/11736790_24
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